Duplicate from shahp7575/gpt-horoscopes

Co-authored-by: Parth Shah <[email protected]>

.gitattributes

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README.md

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+---
+title: Gpt Horoscopes
+emoji: 👁
+colorFrom: purple
+colorTo: pink
+sdk: streamlit
+app_file: app.py
+pinned: false
+duplicated_from: shahp7575/gpt-horoscopes
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

app.py

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+import os
+import warnings
+import requests
+import torch
+import streamlit as st
+from streamlit_lottie import st_lottie
+from transformers import AutoTokenizer, AutoModelWithLMHead
+
+warnings.filterwarnings("ignore")
+
+st.set_page_config(layout='centered', page_title='GPT2-Horoscopes')
+
+def load_lottieurl(url: str):
+    # https://github.com/tylerjrichards/streamlit_goodreads_app/blob/master/books.py
+    r = requests.get(url)
+    if r.status_code != 200:
+        return None
+    return r.json()
+
+lottie_book = load_lottieurl('https://assets2.lottiefiles.com/packages/lf20_WL3aE7.json')
+st_lottie(lottie_book, speed=1, height=200, key="initial")
+
+st.markdown('# GPT2-Horoscopes!')
+st.markdown("""
+Hello! This lovely app lets GPT-2 write awesome horoscopes for you. All you need to do
+is select your sign and choose the horoscope category :)  
+""")
+st.markdown("""
+*If you are interested in the fine-tuned model, you can visit the [Model Hub](https://huggingface.co/shahp7575/gpt2-horoscopes) or 
+my [GitHub Repo](https://github.com/shahp7575/gpt2-horoscopes).*
+""")
+
+
+@st.cache(allow_output_mutation=True, max_entries=1)
+def download_model():
+    tokenizer = AutoTokenizer.from_pretrained('shahp7575/gpt2-horoscopes')
+    model = AutoModelWithLMHead.from_pretrained('shahp7575/gpt2-horoscopes')
+    return model, tokenizer
+model, tokenizer = download_model()
+
+def make_prompt(category):
+    return f"<|category|> {category} <|horoscope|>"
+
+def generate(prompt, model, tokenizer, temperature, num_outputs, top_k):
+
+    sample_outputs = model.generate(prompt, 
+                                    #bos_token_id=random.randint(1,30000),
+                                    do_sample=True,   
+                                    top_k=top_k, 
+                                    max_length = 300,
+                                    top_p=0.95,
+                                    temperature=temperature,
+                                    num_return_sequences=num_outputs)
+
+    return sample_outputs
+    
+with st.beta_container():
+
+    horoscope = st.selectbox("Choose Your Sign: ", ('Aquarius', 'Pisces', 'Aries',
+                                                         'Taurus', 'Gemini', 'Cancer',
+                                                         'Leo', 'Virgo', 'Libra', 
+                                                          'Scorpio', 'Sagittarius', 'Capricorn'), index=0)
+    choice = st.selectbox("Choose Category:", ('general', 'career', 'love', 'wellness', 'birthday'),
+                                    index=0, )
+
+    temp_slider = st.slider("Temperature (Higher Value = More randomness)", min_value=0.01, max_value=1.0, value=0.95)
+
+if st.button('Generate Horoscopes!'):
+    prompt = make_prompt(choice)
+    prompt_encoded = torch.tensor(tokenizer.encode(prompt)).unsqueeze(0)
+    with st.spinner('Generating...'):
+        sample_output = generate(prompt_encoded, model, tokenizer, temperature=temp_slider, num_outputs=1, top_k=40)
+        final_out = tokenizer.decode(sample_output[0], skip_special_tokens=True)
+        st.write(final_out[len(choice)+2:])
+else: pass
+
+

requirements.txt

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+numpy
+pandas
+requests
+streamlit==0.80.0
+streamlit-lottie==0.0.2
+torch
+tqdm
+transformers